An electrocardiogram (ECG) is a test that records the electrical activity of the heart as recorded by electrodes attached to the outer surface of the skin. Impedance variation between the recording electrode and the skin due to respiration or other body movement can cause baseline variations (also referred to as low frequency wander) in the ECG signal. Baseline variation is one type of noise in electrocardiogram signals. FIG. 1 is a plot 100 showing an example ECG signal containing baseline variation. QRS complexes 110 can be identified by sharp spikes in the signal.
There are a variety of methods for baseline removal from the ECG, including high-pass filtering, adaptive filtering, wavelet transform, time-frequency analysis, curve fitting, etc. One approach, which is a special type of curve fitting, is the cubic spline method. A cubic spline is fitted on isoelectric reference points to estimate the baseline. The cubic spline method can be prone to error in the calculation of the isoelectric reference points, especially in the presence of noise.
ECG baseline variation can comprise a low frequency signal within a range of 0 to 0.8 Hz. According to the American Health Association (AHA), the frequency in the ECG signal is typically above 0.05 Hz. Since the frequency band of the baseline noise overlaps with the ECG signal of interest, a simple high-pass filter is not sufficient for removing the baseline.
Another approach to baseline removal is to use a high-pass filter. However, since the baseline is a type of in-band noise, a cut-off frequency cannot be set that would completely separate the ECG signal from the baseline. An approach adapting the cutoff frequency of the baseline filter to the heart rate was introduced by L. Lundstrom in 1995. According to Fourier theory, the frequency spectrum of a periodic signal is non-zero only on the base frequency and harmonics. This means that if the period is T, the lowest frequency is 1/T. An ideal ECG, which has constant heart rate and identical morphology for each heart beat, can be treated as a periodic signal, such that the lowest frequency is HeartRate/60 (Hz). If the cutoff frequency is set to this value, the low frequency noise can be removed. However, when the heart rate is low, this approach can not remove the baseline variation completely.